Glossary

“Cooperstown Cred” features a blend of traditional statistics, the ones we grew up with (batting average, RBI, wins, losses) with advanced metrics like OPS+, ERA+ and WAR. The industry of sabermetrics is growing rapidly and the internet now puts information at our fingertips that was previously accessible only through massive tomes like the MacMillan Baseball Encyclopedia.

There are many websites devoted to the baseball statistics. For Cooperstown Cred, we rely almost exclusively on Baseball Reference. Besides being a full encyclopedia of every player in the history of the game, it has tools that allow the user to create leader-boards of almost anything you can think of. If you want to know who has the highest home-road OPS differential, you can find it. If you want to know who had the most RBI over a ten year period, you can find it. Fan Graphs is another excellent site with some next-level information.

Abbreviations:

Accolades:

MVP = Most Valuable Player

CY = Cy Young

GG = Gold Glove Awards won

ASG = All Star Games

From 1959-1992 there were two All-Star Games played per year so sometimes we’ll refer to “All-Star Years” to not give a player double credit for the two games that year.

Advanced Metrics:

OPS+: This is an adjusted version of OPS (which is On-Base% + Slugging%). In recent years, OPS has started to replace Batting Average as the go-to “rate” statistic. Until recently, every televised baseball game would show a batter’s batting average, home runs and RBI. Batting average (as a rate stat) is easy to understand. Today, some telecasts will also show a player’s On-base% or their OPS. What OPS+ does is adjust the OPS of each player to account for ballpark effects and also the overall hitting-friendliness of the era in which the player appeared. Common sense tells us that a member of the Colorado Rockies has a hitting advantage over a member of the San Diego Padres. It’s the mile high air vs the marine layer. In addition, certain changes in the history of the game made it easier or more difficult to hit. Whether its ballpark sizes, the height of the mound or the core of the ball itself, every year is different. OPS+ put it on the same playing field.

OPS+ also serves to make OPS a more easily understood statistic. As baseball fans, we’re conditioned to know that a .300 batting average is good and a .225 average is bad. But do we all intuitively know what’s a good number for OPS? Future generations of baseball fans undoubtedly will but OPS+ sets 100 as “average.” Therefore, if you’re above 100, your OPS is above average, if it’s lower, you’re below average.

One limitation of OPS+ should be noted. It does not account for platoon splits within a particular ballpark. So, to use the best example, all three incarnations of Yankee Stadium have featured a short right-field fence. The first two versions included massive gaps in left-center field. Therefore, the right-handed hitting Joe DiMaggio’s still-excellent career 155 OPS+ almost certainly understates his value. The ballpark calculation for OPS+ covers just the ballpark trends as a whole, not as it relates to left-handed hitters vs right-handed hitters. DiMaggio’s career was shortened by his military service in World War II but still, his career total of 361 home runs was deflated by Yankee Stadium (he hit 213 taters in road games, just 148 at home).

ERA+: This is the pitching version of OPS+. As it is with a hitter’s Batting Average, ERA is a statistic that most baseball fans understand in that it represents “Earned Runs allowed per 9 innings.” So, if a pitcher has an ERA of 3.00, you would expect them to give up 3 earned runs in a 9 inning game. ERA+ adjusts the traditional ERA statistic for ballpark effects and the overall pitching environment in the era that each hurler toed the rubber. ERA+ is set so that 100 is league average. Therefore, if your ERA+ is over 100, you’re above average, it’s below 100, you’re below average.

The ballpark factors are obvious to understand: it’s easier to post a low ERA at Dodger Stadium then at Coors Field. But the friendliness of each baseball year to hitters or pitchers is relevant too. It was easier to post a low ERA in the dead ball era (pre 1918) or in the high-mound era (1962-1968) than the PED era, where dozens of hitters were fueled by steroids or other Performance Enhancing Drugs.

A great apples to apples comparison can be seen with the great Dodgers lefties Sandy Koufax and Clayton Kershaw. In the last 6 years of his career (1961-1966), Koufax posted a 2.19 ERA (which came out to an ERA+ of 156). Fifty years later (from 2011-2016), Kershaw put up an ERA of 2.06 with an ERA+ of 178. So his ERA was slightly better but his ERA+ was significantly higher because it was tougher to get outs from 2011 to 2016 than from 1961-1966.

An even more telling example would be to compare Koufax to Pedro Martinez at their peaks. Each Hall of Famer had a four-year stretch in which they won 3 Cy Young Awards (Koufax’s was from 1963-1966, Pedro’s from 1997-2000). Sandy had a 1.86 ERA for those years; Pedro’s ERA was 2.16 for his four best. So, without any adjustments, Koufax’s four years were better. But, when adjusted for the eras in which they toiled, Koufax’s ERA+ checks in at 172 (still incredibly great, 72% better than average). But Martinez’ four-year run reflected an ERA+ of a ridiculously high 219. Simply put, posting a 2.16 at the height of the PED era (and with three of those four seasons pitching in Fenway Park) is more impressive than posting a 1.86 ERA at Dodgers Stadium in the 1960’s.

The limitation of ERA+ is the same as it is for ERA. The rules about earned runs sometimes unduly benefit or punish a pitcher. If a pitcher gets two outs and then the next batter reaches base on an error, all runs for the rest of that inning are considered unearned. So you could give up six home runs in a row after that error and all of those runs would be unearned. For this reason, some analysts like to use the stat RA9, which is calculated exactly like ERA except that all runs are counted.

Wins Above Replacement (WAR): perhaps the most controversial advanced metric because a good number of writers and commentators have decided to use it as the be-all, end-all baseball statistic. It is designed to be a single number that represents how many additional wins a player’s team could expect to gain from that player’s presence as opposed to a “replacement” player from the minor leagues. A player whose statistics yield 5 “wins” above replacement would typically be considered an All-Star and a player with a WAR of 8 or higher would be an MVP candidate. It’s a statistic that’s easy to understand in terms of its meaning but difficult to comprehend in terms of how it’s calculated. Think of it as the “passer rating” stat of Major League Baseball. For decades, we’ve been told about a quarterback’s passer rating without understanding the math behind it. We just know its important and trust it.

One key thing to understand about WAR is that it is a counting stat, not a rate stat. The more years you play, the higher your WAR is likely to be. This is different than stats like Batting Average and ERA where a player can start going downhill in the later years of their career. WAR is, however, a counting stat in which you can count backwards. Some players, still on the field late in their career due to reputation, are actually playing at such an inferior level that their WAR is below zero. Hall of Fame pitcher Steve Carlton is a great example of this. In his final three seasons (ages 41-43), Lefty bounced around five different teams, compiling a 5.72 ERA and a -3.2 WAR. Still, in most cases, you’re going to have a higher WAR just by playing longer.

The one great benefit of WAR is that is the one and only statistic in which you can actually compare position players to pitchers. Needless to say, the way that its calculated for batters and pitchers is entirely different. Here’s the basic methodology for each:

WAR for Position Players: there are six components that make up WAR for a position player. If you’re a rocket scientist, a fully detailed breakdown of how these components are calculated can be found here on Baseball Reference. For the rest of us, this will help us understand how the numbers add up.

Rbat (WAR Runs Batting): for each position player, this number represents the number of runs above or below average a hitter is. Since this number is compared to an “average” MLB player (not a replacement level player from the minor leagues), many hitters will be in negative territory here. There are, in fact, a full 10 Hall of Fame position players who are negative in “Runs Batting.” This doesn’t necessarily mean that these were bad Hall of Fame selections (Ozzie Smith is one of the ten) but it does mean that they’re in the Hall because of their fielding or running ability.

Rfield (WAR Runs Fielding): this number represents the number of runs above or below average a position player was in the field. Again, this number is compared to an average MLB player so many players will be negative here. Of the 153 position players in the Hall of Fame through the class of 2017, 41 of them were defensive liabilities to some degree. This isn’t that stunning because we all know that a great many hitters are in the Hall because of their prowess with the bat, not the glove. Rfield is the most controversial of the WAR components because of some shocking numbers. For instance, the numbers say that Roberto Alomar (owner of 10 Gold Gloves at 2nd base) was minus 36 runs as a defensive player. This is the statistic that people cite to say that Derek Jeter is the worst defensive player in the history of baseball. He’s not the worst, really, because most truly awful defenders couldn’t hit nearly well enough to accumulate over 11,000 plate appearances. My own feelings about Rfield is that it should be considered fairly reliable after the year 2003 (when Baseball Info Solutions introduced “Defensive Runs Saved”) but, for years prior, should be viewed upon with a level of skepticism.

Rbaser (WAR Runs Baserunning): this represents the number of runs above or below average a player was on the base paths. It includes stolen bases, times caught stealing but also the number of extra bases taken and outs made on the basepaths. An Extra Base Taken (XBT) is defined as going from first to third on a single or first to home on a double. An out on the basepaths defines itself.

Rdp (WAR Runs Grounding into Double Plays): because a double play is a uniquely damaging out, it has its own category. It’s a small subset of hitting situations so its impact on a player’s overall WAR is less here than it is for Rbat, Rfield or Rbaser but it still can be significant. Because its easier to turn double plays on balls hit to the left side of the infield, right-handed batters tend to ground into double plays more often. The bottom seven Rdp members of the Hall all swung the bat from the right side.

Rpos (WAR Runs from Positional Scarcity): this is an adjustment based on the defensive position occupied by each player. It’s an old baseball adage that you have to be “strong up the middle” (the “middle” being catcher, 2nd base, shortstop and center field). Rpos takes this into consideration. This is a subjective component in what is otherwise an objective methodology. The number of added or subtracted “runs” by positional adjustment is somewhat arbitrary. Making this more complicated is the relative importance of defensive excellence at different times in history. In today’s game, defense is less important than ever because so many more at bats end in strikeouts or walks than ever before. Rpos does take this into account. The positional adjustment is, in most cases, less today than it was in yesteryear.

Rrep (Runs from Replacement Level): this is simply the level of additional runs that a player is expected to be than a replacement level player based solely on playing time. This is based on plate appearances only, not by position. It’s based on the concept that being able to suit up every day is worth something. It’s the one component of WAR that has only positive numbers, no negatives.

For positional WAR, you can go to Baseball Reference and add these six components to get “Runs above Average” (RAR), the basis from which WAR is calculated.

Offensive WAR (oWAR): this takes all of the elements of a position player’s Total WAR but excludes defense. It includes batting, base-running, DP avoidance and also has the positional adjustment. If you don’t trust the defensive metrics, you can look at oWAR to simply see how valuable a player was on the offensive side of the game.

Defensive WAR (dWAR): this takes only the player’s defensive contributions and positional adjustment into account in a WAR calculation.

NOTE: if you add oWAR and dWAR together it will NOT get you a player’s overall WAR because it would take in the positional adjustment twice.

WAR for Pitchers: as impossible as WAR for position players is to calculate for a lay-person, WAR for pitchers is even more complex because you can’t just add up the differing components. Let’s briefly go through some of the components that go into a pitchers’ WAR. The full NASA-level of details can be linked here on Baseball Reference.

RA9: simply the runs allowed by the pitcher for every nine innings. This is the same as ERA except that unearned runs are also counted. As we’ll, the quality of a pitcher’s team defense behind him is taken into account elsewhere.

RA9opp: the average number of runs scored by a pitcher’s opposing team, per 9 innings. Not all opponents are created equal. For a single year, one pitcher might get the luck of the draw, toeing the rubber against the worst hitting teams while another might draw the short straw with juggernaut offensive teams. These things tend to ever out in the long term but not always. A recent example is to compare Mike Mussina, who spent his entire career in the rugged A.L. East and Tom Glavine, who pitched exclusively in the less offensively prolific N.L. East. Glavine’s career RA9def was 4.54, Mussina’s was 4.94. That’s a difference of 0.4, just under one full half a run per 9 innings. With numbers we understand, Mussina’s 3.68 career ERA is thus more impressive than Glavine’s 3.54 (and this is reflected in their respective numbers for ERA+. Mussina’s (123) is higher than Glavine’s (118)

RA9def: runs per 9 innings of support (or lack thereof) from a player’s defense. This puts a pitcher’s performance in the context of the overall defensive numbers of his team. When you find a pitcher with a surprisingly high or low WAR, this is the first place to look to see why.

RA9role: gives more credit to being a starting pitcher than a relief pitcher.

PPFp: adjusts for the ballparks in which a pitcher threw. Unlike a position player, whose road starts will typically be split around the league, a pitcher might, by luck of the draw, have a disproportionate number of starts in pitcher-friendly or unfriendly starts.

One thing that trips people up sometimes with pitchers is that they have two aspects of the game that contribute to their WAR. The biggest component by far is how they perform on the mound. However, in today’s National League, in interleague games in N.L. and in all of baseball before 1973, pitchers also have had to swing the bat.

Hall of Fame pitcher Red Ruffing had a career pitching WAR of 55.4, which is on the low end of starting pitchers enshrined in Cooperstown, although certainly not the lowest. His career ERA of 3.80, on the other hand, is the highest for any inducted pitcher. Ruffing, a member of six World Champion team with the Yankees, also was a decent hitter and was used as a pinch-hitter over 250 times. In his career, he hit .269 with 36 home runs and 273 RBI for a rate of 7 HR and 50 RBI for every 162 games. Due to the positional adjustment (the value of being a good-hitting pitcher), Ruffing’s career batting WAR was 15.0. That would put his overall WAR at 70.4, which theoretically would move him from a questionable Hall of Famer to an indisputable one.

An amazing thing to contemplate: because of the value of being a pitcher, Ruffing’s batting WAR is higher than that of the Philadelphia Phillies’ Ryan Howard (14.9 WAR), who hit 382 major league home runs. It’s also higher than Bill Buckner’s lifetime WAR (14.8), despite his 2,715 career hits.

NOTE for this site: when showing lists of pitchers and their WAR, we’re focusing solely on their WAR as pitchers. In the vast majority of cases, the hitting value that a pitcher adds is functionally irrelevant to whether they deserve a Hall of Fame plaque or not.

Win Probability Added (WPA): this is a statistic that takes every play during every game into the context in which it occurred. If you hit a grand slam home run in the 9th inning of a game in which your team is leading 10-0, you’ve added virtually nothing to the likelihood that your team will win that game. If, on the other hand, you do it with two outs in the bottom of the 9th inning and your team trailing by three runs, you’ve turned a almost certain defeat into a victory.

WPA is calculated for batters, pitchers and base-runners. Let’s take a example: in the 1988 World Series, Kirk Gibson hit a two-out, two-run home run off Dennis Eckersley to give the Los Angeles Dodgers a 5-4 Game 1 victory over the Oakland A’s. For that home run, Gibson’s WPA was 0.87. That means that, statistically speaking, the Dodgers had a 13% chance of winning the game. Gibson’s home run elevated those chances from 13% to 100%. By the way, if you feel like that 13% exaggerates the Dodgers’ chances in that game, WPA doesn’t take into account the quality of the opponent so Eckersley’s greatness is not reflected. Also, remember, the tying run was on 2nd base so a bloop hit could have tied the game and anything could have happened after that.

Gibson’s WPA was 0.87 in that game. Eckersley’s WPA was -0.83. When he entered the game with a one run lead on the road, his team’s chances of winning were 83%. In the course of that inning the A’s went from 83% to zero, hence -0.83.

On this site, we will most often use WPA with respect to relief pitchers. Because they pitch so much fewer innings than starters, the value of relievers can’t be measured by Wins Above Replacement (WAR), which is a “counting” stat in which total innings matters. WPA is especially important for closers because it shows the impact of the player’s performance on his team’s chance to win the game. To put this into focus, Trevor Hoffman, who is on the 2018 Hall of Fame ballot, is 20th all-time in WPA but, because he was a relief pitcher, just 209th in career WAR for pitchers.

Similarity Scores: an invention by sabermetric pioneer Bill James, “Similarity Scores” are a quick and easy way to compare two player and they are available on Baseball Reference for most players in history. He introduced a version of this in his 1986 Baseball Abstract and then refined the system in his 1994 book The Politics of Glory, which to me is the greatest book about the Hall of Fame ever written.

The Similarity Score concept is that if two players had absolutely identical statistics for one season (or even for an entire career), their similarity score would be 1,000. Of course the odds of this happening with any reasonable sample size are infinitesimal. Therefore, the system deducts a point for each statistical discrepancy. So, if Player A has 15 more hits than Player B, one point is deducted. If Player A has 30 more hits than Player B, 2 points are deducted, and so on.

For batters, 13 statistical categories are used. The numbers in parentheses after these categories is the differential required to deduct a point. For instance, for every difference of 20 in total games played, one point deducted. The categories for position players are Games (20), At Bats (75), Runs (10), Hits (15), Doubles (5), Triples (4), Home Runs (2), RBI (10), Walks (25), Strikeouts (150), Stolen Bases (20), Batting Average (.001), Slugging Percentage (.002).

There’s a positional value adjustment as well.

240 – Catcher

168 – Shortstop

132 – Second Base

84 – Third Base

48 – Outfield (James distinguishes, but I don’t have that data incorporated at the moment)

12 – First Base

0 – DH

If one player is a catcher and the other is a shortstop, 72 points are deducted (the difference between 240 for catcher and 168 for shortstop). If you’re wondering why a catcher is considered “most similar” to to a shortstop (as opposed to first base, which is where the best hitting catchers wind up), let me explain. It’s about positional value on the defensive spectrum.

The example of the “most similar” players James could find was 1970’s first basemen Andre Thornton and John Mayberry, who had Similarity Scores (to each other) of 964.8. Look at their numbers: